Evidence map›Paper›PMID 42483502›Full record

ArticleFrontiers in plant science2026

Integration of widely targeted and targeted metabolomics reveals flavonoid accumulation profiles across different cultivars of

Luan Li, Junjie Yang, Tianxiang Zhang, Kunxiu Cai, Fenfen Wang, Qi Yang, Xiuxiang Lin, Ying Chen, Tao Zheng

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In one paragraph

Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Luan Li *Party and Government Office, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Junjie Yang *Public Laboratory, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Tianxiang ZhangBiotechnology Laboratory, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Kunxiu CaiBiotechnology Laboratory, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Fenfen WangPublic Laboratory, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Qi YangBiotechnology Laboratory, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Xiuxiang LinFruit and Vegetable Laboratory, Fujian Institute Of Tropical Crops, Zhangzhou, China.
Ying ChenCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Tao ZhengParty and Government Office, Fujian Institute Of Tropical Crops, Zhangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Methods: We employed an integrated approach combining widely targeted and targeted metabolomics data to systematically elucidate the metabolic profile differences among five major Results: A total of 2,286 metabolites were identified, from which 802 differential metabolites were identified, with the majority belonging to flavonoids, lipids, and terpenoids. Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) revealed that the metabolic profiles of the XGH and YL cultivars were significantly distinct from the others. KEGG pathway enrichment analysis indicated that phenylpropanoid biosynthesis, flavonoid biosynthesis, and flavone and flavonol biosynthesis are the core pathways driving cultivar differentiation. Additionally, three common differential Kaempferol-4'-O-glucoside*, 1-O-(3,4,5-Trimethoxybenzoyl)-β-D-Glucopyranoside, and sec-o-Glucosylhamaudol were identified as potential key chemical markers for cultivar discrimination. Targeted quantitative analysis further validated that XGH and YL possess a significant advantage in the accumulation of 11 key flavonoid components, with flavonol glycosides exhibiting the most prominent accumulation characteristics. Discussion: This study represents the first system-level investigation into the metabolic diversity of

Indexed as

cultivar differentiationflavonoidsLudisia discolorquality evaluationtargeted quantificationwidely targeted metabolomics

Identifiers

PMID42483502
PMCPMC13385630

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